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Table 3 Mean annual wind speed for the selected stations in the Kurdistan province (m/s) Height Station 10 m 20 m 40 m Bijar 4.12 4.77 5.56 Saghez 2.29 2.74 3.24 Sanandaj 2.07 2.47 2.95 Ghorveh 3.24 3.78 4.44 Zarineh Obato 3.70 4.30 5.04. Figure 2 shows the average of monthly wind speed for 10, 20 and 40 m at Bijar.
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To confirm an enhanced DEM in EGYPT, the two orthometric height models (SRTM1 ellipsoidal height + EGM96) and (SRTM1 ellipsoidal height + GECO) are assessment with 17 GPS/leveling stations and 112 orthometric height stations, the results show that the estimated height differences between the SRTM1 before improvements and the enhanced model are at rate of 0.44 m and 0.06 m respectively.
The original surface pressure measured at CTGR (P CTGR, black solid line in Figure 4) was converted to the pressure at the height of station 96745 (P 96745, orthometric height 8 m) by using the following relationship, derived from the barometric formula in Berberan-Santos et al. ( 1997) P 96745 = P CTGR exp - g M d ( H 96745 - H CTGR ) R ∗ T ISA (13).
The integrated Geno Kalman Filtering (GKF) technique is applied to develop predictive models for estimation of significant wave height at stations LZ40, L006, L005 and L001 in Lake Okeechobee, Florida.
where hBSand hMSare the height of base station and mobile station, respectively.
Table 2. Maximum tsunami heights for stations located from north (top) to south (bottom).
A spectral analysis of DORIS station height time series indicates that annual and semi-annual signals are dominant.
Also, it was asked about the equipment characteristics, namely: control station height, accessibility of the monitor, accessibility of compression devices, accessibility of the compression paddles and intensity of the positioning light.
The following formula is a first-order approximation for the relationship between pressure and altitude (Jin et al. 2007): {log}_{10}papprox 5-frac{h}{15.5} (18) Fig. 13 Correlations between GNSS-PWV versus Mean Sea level height of GNSS station on randomly selected day (15 March 2017).
Analogously to the preprocessing in section 2, the surface pressure is extrapolated exponentially to the station height using the virtual temperature from GPT2.
From those delay errors due to pressure differences, the bias and standard deviation of the station height errors can be inferred.
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Justyna Jupowicz-Kozak
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